Instructor:

Mabel Trafford

School:

University of Hawaii

Semester:

Summer 2010

Description:

This course will cover the most important healthcare related information resources within a context of providing reference and information services. It will cover primary, secondary and tertiary sources in the following areas: medical, dental, pharmacy, nursing, allied health, consumer health and informatics. We will look at evidence based medical and nursing information resources in terms of when and how to use them most effectively. We will learn about the National Library of Medicine’s Medical Subject Headings (MeSH) thesaurus and the Unified Medical Language System (UMLS). We will also learn how to compare and evaluate similar resources and how to select the best resources. We will learn how to do efficient and effective searches in the major healthcare information resources.

Instructor:

Luz M. Quiroga

School:

University of Hawaii

Semester:

Spring 2013

Description:

Reducing information overload is the main goal of Information Filtering (IF) and it has been recognized as one of the priorities in the development of current web-based information systems. IF systems are meant to deliver personalized information, acting as personal information agents that recommend relevant (filtered) documents based on their clients’ information preferences and needs (profiles).

Recommendation technology is being presented as a new paradigm of search where relevant items find the user instead of the user explicitly searching for them (http://recsys.acm.org/2009). New trends in Information technologies such as social networking and mobile devices are making personalization research and practice a priority.

Libraries have been offering personalized system in services such as: selective dissemination of information, alerting services for a long time. Customer and marketing research has also a long tradition. With the advances in information technology, personalization has evolved, now covering more sophisticated ways. Collaborative filtering, recommender systems, personalized help systems, social filtering, social data-mining systems, and user-adaptive systems can be collectively called information-filtering (IF) systems. Today, personalization is everywhere, in every industry and service, from marketing to health, travel, education, entertainment, etc.

IF researchers contend that a conceptual framework for the design of IF systems comes from two well established lines of research: Information Retrieval (IR) and User modeling (UM). The course covers theories, research and current practices in these two fields, including modeling and representation of documents, queries, user preferences, and user-system interaction.

The first part of the course includes IR models for searching: set theoretic models (e.g. Boolean model) and algebraic models (e.g. vector model). Emphasis will be given to query languages and protocols as well as to relevance feedback and strategies for query expansion and reformulation using, for example, different types of thesauri, metadata and markup languages (SGML, HTML and XML) that provide information on the document structure, format and semantics will also be included as part of the study of Web Based Information Retrieval and Filtering. Students will learn about system and user based retrieval performance evaluation and will experiment with benchmark tasks and reference test collections.

The second part of the course will mainly focus on user modeling. Although IF could be considered an application of IR, there is a major distinction: the existence of a highly individualized profile that is a representation of relatively stable user information preferences and needs. Profiles can be considered as user models and will be the center of this second part of the course which will review core topics in IF research including user modeling in IR and IF systems, acquisition of user profiles, personal ontologies, IF taxonomies, IF performance evaluation and Personal Information Management (PIM).

Instructor:

Peter Jacso

School:

University of Hawaii

Semester:

Fall 2012

Description:

To study the objectives, principles and methods of evaluating digital information sources (especially databases), for advising users in selecting databases and Web sites most appropriate for their information needs, and for making database licensing decisions.

Link to Syllabus:

Instructor:

Rich Gazan

School:

University of Hawaii

Semester:

Summer 2013

Description:

The goal of this course is for students to gain a functional understanding of information retrieval systems, how they are implemented in a diverse array of Web and professional online databases, and how to search and use them effectively in research and reference work.

Link to Syllabus:

Instructor:

Karyn Moffatt

School:

McGill

Semester:

Winter 2014

Description:

Fundamental aspects of reflective thinking and the methods and techniques of research appropriate to the investigation of library/information problems. Criteria helpful in evaluating published research in library/information studies by analyzing the various steps of the research process, thereby providing guidelines for planning, conducting, and reporting research.